Arabian Journal for Science and Engineering最新文献

This paper proposes a dual-output DC–DC power conversion system based on Photovoltaic (PV) technology. PV panels are connected to a series compensated Buck-Boost Converter (SCBBC) to harvest solar energy, while a sliding mode controller (SMC) ensures maximum power point tracking (MPPT). During the intermediate phase, a synchronized Buck-Boost Converter (SBBC) topology is used to ensure effective charging and discharging of batteries. Additionally, a PI-SMC hybrid control strategy is applied at the back end to the Super Lift Luo Converter (SLLC) to maintain the load voltage at a desired value. A Gravitational Search Algorithm (GSA)-based PI controller controls the input current, while the output voltage is controlled by the outer loop (SMC). We use a single-loop SMC approach to validate the performance of the proposed dual-loop control scheme. According to the presented results, the dual-loop control scheme demonstrated higher dynamic performance in controlling input current and output voltage.

In this work, we fabricated an Ag/Bi₇O₉I₃ composite and tested the composite for the photodegradation of Rhodamine B (RhB) dye under UV–vis light irradiation. XRD, FESEM, TEM, UV–visible absorbance, XPS studies, ESR, and electrochemical analysis were used to characterize the synthesized photocatalysts. The synthesized catalyst displayed a maximum degradation efficiency of 98.45% in the 150-min experiment, which is nearly 1.56 times higher than Bi₇O₉I₃. The enhanced photocatalytic activity of Ag/Bi₇O₉I₃ is attributed to the acceleration of charge separation and transfer of charge carriers with the inclusion of Ag. The improvement in photocatalytic efficiency of Ag/Bi₇O₉I₃ can be attributed to Ag deposition, which acts as an electron sink to avoid recombination of photogenerated electrons and holes. Additionally, Ag nanoparticles may show plasmonic resonance producing more electron–hole pairs in Bi₇O₉I₃. Furthermore, a variety of tests were carried out on Ag/Bi₇O₉I₃ in order to clarify how different factors affect the photodegradation efficiency. The medium with pH = 3, catalyst loading = 35 mg, and Rhodamine B concentration = 10 ppm resulted in highest activity. Using a radical scavenging experiment and ESR studies, the effective radicals in promoting dye degradation have been identified, and ·O₂⁻ radicals turned out to be the main radicals in promoting photocatalysis. Additionally, the reusability and degradation mechanisms of the enhanced photodegradation on the specified photocatalyst were examined.

The quadtree partition process involves major complexity in high-efficiency video coding (HEVC/H.265). It divides the coding tree units (CTUs) recursively into coding units (CUs). Determining the coding unit partition depth based on rate-distortion optimisation is computationally difficult in HEVC. This article proposes a system based on a deep learning architecture for determining the coding unit partition depth with less time in HEVC intra-prediction. The proposed system minimises computing complexity by removing the rate-distortion optimisation. The proposed system comprises two main blocks: the pre-processing block and the deep learning block. During the pre-processing phase, the spatial resolution of the input data is drastically reduced, enabling the neural network model to quickly adapt to the input sample and extract more meaningful feature data. This paper proposes two distinct deep learning architectures, CU-VGG16 and CU-VGG19. Pre-processed coding units (16 (times ) 16) are the input for the deep learning architecture, and the corresponding coding units’ depths (0, 1, 2, 3) are the output. To compare the accuracy of coding unit depth prediction in the two proposed models, we have created a database with varying resolutions. The performance of the proposed models was observed by replacing the CU partition block of traditional HEVC with the proposed systems and comparing the bit rate and encoding time with traditional HEVC. The results demonstrated that the proposed architecture with CU-VGG16 and CU-VGG19 designs speeds up coding unit partitioning by 87.15% and 87.70%, respectively, as compared to standard HEVC.

In this study, three different Switched-Capacitor Enhanced boost quasi Z source (SCEq-Zs) DC–DC converters are presented, out of which the converter having a switched capacitor network positioned in series with the enhanced boost q-Zs network (SCEq-Zs-3) provides the common ground path and less output capacitor stress. This converter has a high voltage conversion ratio with low voltage stress on active and passive devices like capacitors, diodes, and the power semiconductor switch in comparison to other converters. This unidirectional hybrid switched-capacitor with a quasi Z source combination provides continuous and ripple-free source current mostly suitable for fuel cell applications. This leads to reduced voltage fluctuations at the input, providing a steady source of power to the converter. The converter is comprehensively analyzed and the operating principle along with waveforms is presented in this paper. A systematic comparison with other DC–DC boost converters is brought to view. A scaled-down 200V/200W prototype for the suggested converter is developed to verify the results of the theoretical study. A maximum efficiency of 95.85 % is measured. To demonstrate the effectiveness of the suggested converter, detailed experimental findings are presented.

In this study, a new method was developed for extraction and determination of polycyclic aromatic hydrocarbons (PAHs) in biota samples. The biota samples were packed inside a porous membrane bag and subjected to ultrasonication-assisted solvent extraction. This method showed good applicability to both low and high sample weights. The effect of various parameters such as type and volume of extraction solvent, ultrasonication time, sample weight, and dimensions of extraction device on extraction performance was evaluated. The developed method showed a good linear range from 12.5 to 100 ng/g for all the selected analytes with correlation coefficients ranging from 0.9907 to 0.9999. The limits of detection ranged from 0.97 to 3.47 ng/g. The method’s precision was assessed based on relative standard deviations, which were below 13.5% indicating an acceptable precision. The developed procedure used for determination of PAHs in biota samples is characterized by many positive features. The packing of dried biota samples inside the membrane bag is advantageous because it eliminates several steps such as filtration or centrifugation and further extract purification. As the samples are protected inside the membrane bag, they can be easily separated from the solvent extract after the completion of the extraction process by simply removing the membrane bag. Moreover, the membrane may hinder the transportation of macromolecules to the extract, thus resulting in a relatively cleaner extract. Due to its simplicity and excellent figures of merit, this method presents a better potential for routine analysis of polycyclic aromatic hydrocarbons in biota samples.

In situ injectable hydrogels are effectively employed to fill irregular cavitary bone defects with initiating bone growth in targeted areas. Herein, an injectable composited hydrogel composed of collagen and alginate cross-linked in situ using different concentrations of calcium sulfate (0.15, 0.3 and 0.6%, wt./v) was synthesized. Recently, CaSO₄ is frequently supported as a bone graft material for bone regeneration, owing to its biocompatibility and osteoconductive properties. Moreover, hydroxyapatite (Hap) after salinization-step by (3-Aminopropyl) triethoxysilane (APTES) was incorporated for further enhancing the osteoconductive property of injected hydrogels. All fabricated hydrogels were characterized by SEM, FTIR and XRD analyses. While physiochemical characteristics of hydrogels were assessed through swelling index, hydrolytic degradability and thermal stability measurements. In vitro bio-assessments, e.g., antimicrobial activity, cytotoxicity and cell adhesion tests using osteoblast-like cells (MG-63) were investigated. Results showed that addition of Hap offered better control of gelation time and formed uniform hydrogels, additionally improved significantly thermal stability, which leads to hindering of swelling index, prolonging hydrolytic degradability rates and significantly enhanced the antimicrobial activity of hydrogel; compared to hydrogel free-Hap. Hap-loaded Col–Alg–CaSO₄ hydrogel with the highest concentration of CaSO₄ recorded an enrichment of cell viability among all hydrogel samples. Notably, In vitro cell adhesion test showed that MG-63 cells adhered adequately with all hydrogels. The results support the approach of using an injectable Hap-loaded Col/Alg hydrogel cross-linked with CaSO₄ as an alter and novel technique to enhance bone tissue regeneration, host–implant integration, quick/simple technique and easier for clinical handling.

This article presents an experimental investigation of the WEDM (Wire Electrical Discharge Machining) performance of Al-TiB₂ composites fabricated using ultrasonic vibration-assisted stir casting and containing four different weight percentages (1%, 2.5%, 4%, and 5.5%) of TiB₂ particles. Key machining parameters, namely pulse-on time, wire feed rate, and pulse-off time, are varied at three levels suitable for machining aluminium base material while minimizing wire breakage. Cutting speed, material removal rate, and kerf width are observed individually for each selected level of these process parameters. Surface features are assessed using SEM (Scanning Electron Microscope), EDAX (Energy Dispersive X-ray Spectroscopy), 3D optical surface profilometer, and optical microscopy. Notably, the roughness values are lower in the 4% and 5.5% TiB₂ composites compared to the base matrix. This reduction in roughness is due to the protective role of the particles, which shield the surface from melting during the WEDM process. Melting and re-welding phenomena were observed throughout the machining process. It is observed that higher pulse-on time generates harsh sparks, leading to rougher surfaces that include melted zones and pits. The WEDM operations performed on the 5.5 wt% reinforced composite surface result in a significant reduction in roughness, decreasing from around 5 µm to approximately 2.7 µm.

Comfort and safety in automobiles can be enhanced with predictive maintenance by means of early problem detection and isolation, collectively referred to as fault diagnosis. To maintain a lead position in automotive industry, fleet managers are turning to predictive analysis. In this study, an attempt was made involving feature fusion to determine most significant features required to determine the suspension faults using vibration signals and machine learning approach. Three different features extraction techniques such as statistical, histogram and autoregressive moving average model (ARMA) were extracted from the acquired vibration signals for different fault conditions at the three different loads by means of a specially fabricated experimental setup. Feature selection was done for individual features using J48 decision tree algorithm. The performance of tree-based classifiers was assessed on the chosen individual features. Additionally, each individual feature was paired with others in four distinct combinations: statistical-histogram, statistical-ARMA, ARMA-histogram and ARMA-histogram-statistical, across three different loads. These combined features were then input into tree-based algorithms to identify the optimal classification algorithm, regardless of the load conditions. The results obtained in this study indicate that the combination of the ARMA-histogram-statistical feature with a random forest classifier yields optimal classification accuracy, regardless of load conditions, with values of 98.125%, 99.375% and 96.250%, respectively, and an average computational time of 0.10 s.

The phenol-based antioxidants as free radical scavengers are expected to continue increasing as additives in industries. As an antioxidant, lignin has low oxidative stability in pure solid form, so stabilization is needed to produce lignin-based antioxidants. This research focuses on the valorization of alkaline lignin by hydrogenolysis using a Pt/C catalyst and formic acid as a hydrogen donor. Three treatment variables, namely the amount of formic acid (FA), the amount of ethanol (EtOH), and radiation time (T), were observed for their contribution to the three responses, namely the total phenol content (TPC), the degree of depolymerization (DD), and the IC₅₀ value of DPPH as an antioxidants activity. This study found that the best results were obtained at operating conditions FA, EtOH, and T 5 mL, 100 mL, 3 min in sequence, producing TPC, DD, and IC₅₀ worth 4792,055 mg/ L, 23.650%, and 35.860 mg/L, respectively. The results were optimized using the response surface methodology with the Design Expert 11 program with the optimized result being FA, EtOH, and T 10 mL, 100 mL, 3 min consecutively and resulted in TPC, DD, and IC₅₀ of 4987.12 mg/L, 26.451%, and 33.865 mg/L, respectively. The results of this study indicate that OPFEB is a source of lignin that has the potential to produce phenolic compounds, which are sources of renewable fine chemicals based on biomass.

The research on metal oxide nanoparticles (MONs) has witnessed incredible growth in recent decades as they are promising electrode materials for multiple applications. This work presents the hydrothermal synthesis of morphologically different MONs based on zinc, cobalt and cerium metals and their modifications with benzene tricarboxylic acid (BTC) using layer-by-layer assembly method. The simple and modified nanoparticles were structurally characterized by FTIR, XRD, SEM–EDX and TGA. Modified carbon paste electrodes (1% w/w) were fabricated using each of the ZnO, ZnO–Cu–BTC, Co₃O₄, Co₃O₄–Cu–BTC, CeO₂ and CeO₂–Cu–BTC materials separately with graphite powder in paraffin oil using 3 cc portable plastic syringe. The XRD results showed 35.5, 10.8, 14.1, 11.6, 10.2 and 8.6 nm average crystal size for ZnO, ZnO–Cu–BTC, Co₃O₄, Co₃O₄–Cu–BTC, CeO₂ and CeO₂–Cu–BTC, respectively. The electrochemical characterizations of each electrode were performed by EIS as well as CV. The electrochemical surface area of electrodes fabricated from ZnO, ZnO–Cu–BTC, Co₃O₄, Co₃O₄–Cu–BTC, CeO₂ and CeO₂–Cu–BTC materials was calculated to be 153.4, 610.4, 746.1, 951.5, 161.7, and 951.8 cm², respectively. The results from EIS plots indicated that electrodes based on modified metal oxide nanoparticles experienced lesser charge transfer resistance as compared to that in simple metal oxide-based electrodes. All the results indicated that electrodes based on modified MONs provide better surface area, surface coverage, charge transfer coefficients and rate constants as compared to those for simple MON-based electrodes. It is concluded that modification of simple MONs with BTC provided smaller particles size, better structural morphology and redox reactions assistance, making them suitable for better electrochemical applications.